A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Short-Sequence Machine Learning Framework for Predicting Constitutive Relationships of Sand
https://orcid.org/0009-0008-1687-3320
https://orcid.org/0000-0002-5820-4394
https://orcid.org/0009-0008-0870-3460
https://orcid.org/0000-0002-4981-1176
https://orcid.org/0009-0006-5182-567X
Short-Sequence Machine Learning Framework for Predicting Constitutive Relationships of Sand
https://orcid.org/0009-0008-1687-3320
https://orcid.org/0000-0002-5820-4394
https://orcid.org/0009-0008-0870-3460
https://orcid.org/0000-0002-4981-1176
https://orcid.org/0009-0006-5182-567X
Short-Sequence Machine Learning Framework for Predicting Constitutive Relationships of Sand
https://orcid.org/0009-0008-1687-3320
https://orcid.org/0000-0002-5820-4394
https://orcid.org/0009-0008-0870-3460
https://orcid.org/0000-0002-4981-1176
https://orcid.org/0009-0006-5182-567X
Short-Sequence Machine Learning Framework for Predicting Constitutive Relationships of Sand
Geotech Geol Eng
Yao, Xiangchen (author) / Ma, Shuqi (author) / Li, Bo (author) / Liu, Honglin (author) / Bai, Jianbiao (author) / Bai, Ziyi (author)
2025-02-01
Article (Journal)
Electronic Resource
English
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